Practice - Comparing Growth Rates
Practice Questions
Test your understanding with targeted questions
What is time complexity?
💡 Hint: Think about how input size affects the time needed.
Give an example of O(1) time complexity.
💡 Hint: Consider operations that do not depend on the size of data.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is the time complexity of accessing an element in an array?
💡 Hint: Consider operations that involve direct access.
True or False: An algorithm with time complexity of O(n!) is considered efficient.
💡 Hint: Recall how factorial growth behaves with increasing n.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Compare the time complexities: Why might you choose an O(n log n) algorithm over a naive O(n^2) one for sorting?
💡 Hint: Think about the difference in number of comparisons made!
Create your own example of an algorithm and identify its time complexity, explaining why it falls into that category.
💡 Hint: Focus on how many times operations are repeated on average.
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Reference links
Supplementary resources to enhance your learning experience.